Bayesian clinical trials (BCT) are purported to be more efficient in terms of cost and human subjects than existing frequentist methods. At this time, BCTs have been implemented for cancer trials, device trials, and some HIV trials, but are the rare exception in other fields of health research. While traditional frequentist methods are widely understood and accepted in practice, Bayesian methods are not yet fully vetted, and, due to their reliance on heavy computations, have not until recently, been readily accessible in the typical clinical trial setting. This comparative effectiveness study aims to consider applications of Bayesian methodology for the clinical trial in comparison to other analytic alternatives using real-life data. This application proposes a series of side-by-side comparisons between existing frequentist group sequential methods, and newer Bayesian methods of analysis of clinical trials using data from completed cardiovascular trials. The trials vary by size, outcome, impact on their field, and date of original analysis. Investigators will re- analyze the data from each trial using two typical frequentist group sequential plans (Obrien-Fleming and Lan- DeMets alpha spending functions) and several variations of Bayesian analysis with informative, non- informative, and skeptical prior distributions in order to determine the sensitivity of outcome and trial duration to analytic assumptions for both standard group sequential methods and BCTs. At each analysis time point, calculations will be made to determine the probability that there is a clinically relevant effect and probability of futility. Bootstrap sampling with a simulated Null distribution will be used to estimate experiment-wise error rates for each analysis. In addition, at each analysis point over time, conditional power to detect an effect will be calculated. In this way direct comparisons can be made as to the relative effectiveness of the different methods of analysis. Finally, results from all trials will be synthesized to identify the characteristics of a cardiovascular clinical trial for which BCT methods would be more or less advantageous. The results from this study will provide critical information to further the development of analytic techniques for clinical trials and to assess the relative efficiency of Bayesian methods using the innovative approach of real- life data rather than the standard use of simulated trial data. PUBLIC HEALTH RELEVANCE: Traditional frequentist methods for analysis of clinical trials are generally accepted as the gold standard in research practice. Newer Bayesian methods, however, hold great promise for a more efficient analytic approach, thereby lowering the costs of clinical research and enhancing the ethical construct of clinical trials by reducing the length of exposure time to inferior treatment arms. The results of this study will provide valuable information about the true comparative performance of the two methods and help identify the circumstances for which Bayesian approaches may provide advantages over conventional analytic techniques.